AI Server Market Size, Share, & Trends Analysis Report By Processor Type (GPU-based Servers, ASIC-based Servers), By Cooling Technology (Air Cooling, Hybrid Cooling), By Form Factor (Rack-Mounted Servers), By End Use, By Region, And Segment Forecasts, 2025 - 2030

AI Server Market Summary

Major cloud service providers are investing heavily in AI-optimized server infrastructure to cater to the growing number of enterprises seeking AI-as-a-service solutions. These deployments often involve custom server architectures, which allow for better energy efficiency and computational throughput. Moreover, as organizations shift toward hybrid and multi-cloud strategies, the need for scalable, AI-optimized server systems within data centers becomes even more critical, supporting both centralized training and edge inferencing scenarios.

The rapid adoption of generative AI applications across various industries is driving AI server market growth. From content creation and customer service automation to personalized marketing and drug discovery, generative AI is pushing the boundaries of compute-intensive operations. These applications require highly specialized server architectures capable of supporting massive parallelism and fast data throughput. The surge in demand for generative models like GPT and DALL·E is compelling enterprises and cloud providers to invest heavily in AI servers that can manage such computational intensity with speed and reliability.

The rise of hybrid and multi-cloud strategies is also accelerating the deployment of AI servers. Enterprises are opting for flexible infrastructure models that allow seamless integration between on-premises systems and public cloud platforms. Artificial intelligence (AI) servers designed for hybrid deployments must be highly adaptable, scalable, and secure to ensure smooth data mobility and unified AI workloads across diverse environments. This flexibility is crucial for organizations looking to optimize cost efficiency, performance, and regulatory compliance when deploying AI solutions at scale.

Cybersecurity and data privacy concerns are further fueling the need for on-premises AI servers. As organizations become increasingly reliant on AI for handling sensitive information such as biometric data, financial records, and proprietary business intelligence, there is growing reluctance to process such data in public cloud environments. On-prem AI servers offer the control and security needed to meet strict compliance standards like GDPR, HIPAA, and PCI-DSS, making them indispensable for industries such as healthcare, finance, and defense.

Moreover, the growth of AI chipsets and system-on-chip (SoC) technologies is transforming the design and capabilities of AI servers. Innovations in AI-specific hardware are leading to more compact, energy-efficient servers that can deliver unprecedented levels of performance. These new designs enable edge computing capabilities without compromising on processing power, and they open up possibilities for AI deployment in environments previously deemed impractical, like mobile units, remote locations, or disaster recovery sites. The continuous advancement of AI hardware is thus a foundational driver pushing the server market forward.

Processor Type Insights

The GPU-based servers segment accounted for the largest revenue share of over 52.0% in 2024. The rise of large language models (LLMs) and generative AI systems is driving the segment growth in the AI server market. Models like GPT, BERT, and DALL·E depend on high throughput and low latency during training and deployment, both of which are efficiently addressed by advanced GPU architectures such as NVIDIA’s A100 and H100. As enterprises integrate these models into customer service, content creation, and predictive analytics, demand for GPU-based servers has surged, especially among cloud providers and data-intensive industries.

The ASIC-based servers segment is anticipated to grow at the highest CAGR during the forecast period. The increasing demand for energy-efficient computing is a major driver for ASIC adoption in the AI server market. As AI workloads scale, so too does the energy requirement to process massive datasets and complex models. ASICs, by design, consume significantly less power than their GPU or CPU counterparts for equivalent workloads. This makes them an ideal solution for data centers and enterprises focused on reducing operational costs and meeting sustainability goals. With hyperscale data centers under pressure to optimize performance per watt, ASIC-based servers are increasingly favored in large AI deployments.

Cooling Technology Insights

The air cooling segment dominated the market and accounted for a revenue share of over 65.0% in 2024. The rising number of edge AI applications is also boosting demand for air-cooled systems. Many edge data centers or modular deployments operate in environments where liquid cooling infrastructure is impractical or unavailable. Air cooling solutions, with their simpler installation and operational flexibility, are better suited for such distributed setups. As AI becomes more pervasive across smart cities, autonomous systems, and industrial automation, compact and efficient air-cooled servers are increasingly being deployed at the edge to enable real-time processing and decision-making.

The hybrid cooling segment is expected to register a significant CAGR from 2025 to 2030. The advancement of high-performance AI chips, including GPUs and custom ASICs, is pushing thermal management to new frontiers. These chips generate concentrated heat loads that exceed the limits of conventional cooling systems. Hybrid solutions, which integrate direct-to-chip liquid cooling with ambient air handling, offer a robust response to this challenge. They ensure the stable operation of high-density AI clusters, preventing thermal throttling and maximizing the chips' computational throughput. This is a critical factor for real-time analytics, machine learning training, and complex simulations.

Form Factor Insights

The rack-mounted servers segment dominated the market and accounted for a revenue share of over 39.0% in 2024. The growing emphasis on modular and space-efficient data center architectures is a key factor fueling the demand for rack-mounted AI servers. As AI adoption spreads across industries, data centers are being designed or retrofitted to support higher-density computing without expanding physical space. Rack-mounted servers allow for efficient stacking and cable management, which not only simplifies deployment but also optimizes airflow and power consumption. These characteristics make them a preferred choice for enterprises looking to enhance their AI capabilities while maintaining operational efficiency and cost-effectiveness.

The blade servers segment is expected to register the highest CAGR from 2025 to 2030. The rise in the adoption of converged and hyper-converged infrastructure in support of AI initiatives is promoting the use of blade servers. Their integration into such architectures allows for centralized control and streamlined deployment of resources, which helps in optimizing performance across compute, storage, and networking components. Enterprises looking to implement AI-driven analytics or intelligent automation in a simplified, cohesive environment are increasingly turning to blade server solutions to meet these needs. This is particularly relevant in sectors like manufacturing and telecommunications, where large-scale data processing and analysis are fundamental to operational advancement.

End Use Insights

The IT & telecommunication segment accounted for the revenue share of over 26.0% in 2024 in the AI server industry. The shift towards edge computing is driving the adoption of AI servers in the IT & telecommunications segment. As networks evolve to support IoT devices and real-time services like augmented reality (AR), virtual reality (VR), and autonomous vehicle communication, telecom companies require AI servers at the edge to ensure immediate data processing and minimal latency. This shift is critical to support next-generation services and reduce the burden on central data centers. AI servers, especially those designed for edge deployments, are becoming essential to telecom providers aiming to deliver seamless, intelligent connectivity to customers and businesses alike.

The retail & e-commerce segment is anticipated to register a CAGR of 39.0% during the forecast period. The need for fraud detection and cybersecurity has prompted e-commerce platforms to deploy AI algorithms capable of identifying and mitigating threats in real-time. These advanced threat detection systems run best on specialized AI servers that can handle rapid data processing and analysis. As cyber threats become more sophisticated, the demand for secure and responsive infrastructure increases accordingly.

Regional Insights

North America AI server market dominated the global market and held the major revenue share of over 37.0% in 2024. The surge in data generation from connected devices, enterprise applications, and digital services is creating an unprecedented need for powerful data processing capabilities. AI servers, especially those equipped with GPUs and other specialized hardware, are being deployed in data centers across North America to manage this growing data deluge. The region’s advanced cloud ecosystem further boosts demand as cloud providers increasingly offer AI as a service, which relies on the deployment of high-capacity AI servers.

U.S. AI Server Market Trends

The U.S. AI server market is projected to grow during the forecast period. The U.S. AI server market benefits from a robust ecosystem of semiconductor and server hardware providers. Companies like NVIDIA, AMD, Intel, and emerging AI chip startups such as Cerebras and Groq are introducing innovative processors optimized for AI workloads. The availability of cutting-edge components domestically reduces supply chain friction and encourages wider adoption of AI servers across industries. These advances also allow for greater customization and scalability, which is particularly valuable for enterprises building AI capabilities tailored to niche applications or verticals.

Europe AI Server Market Trends

The AI server market in Europe is expected to grow at a CAGR of 38.9% from 2025 to 2030. Europe's automotive industry, especially in Germany and France, is a major contributor to the AI server market growth. The development of autonomous driving systems and smart mobility solutions requires immense computational power, typically delivered by high-performance AI servers. As these technologies progress from pilot phases to real-world deployment, the infrastructure to support real-time data processing and AI model training is expanding rapidly, driving investment in both centralized and edge-based AI server installations.

The AI server industry in Germany is expected to grow during the forecast period. Germany’s emphasis on data protection and digital sovereignty further contributes to the growth of the domestic AI server market. With strict enforcement of the General Data Protection Regulation (GDPR), organizations are prioritizing in-country data processing and storage. This necessitates local deployment of AI infrastructure, including servers capable of handling complex analytics and machine learning workloads while maintaining compliance. As organizations seek to keep sensitive data within national borders, demand for AI servers hosted in German facilities is on the rise.

Asia Pacific AI Server Market Trends

The demand for the AI server market in the Asia Pacific is expected to be the fastest-growing region with a CAGR of 40.6% from 2025 to 2030. The region’s fast-growing e-commerce and digital entertainment industries are driving the need for AI-enhanced customer experiences. Online retail platforms in the Asia Pacific markets use AI servers to support recommendation engines, fraud detection systems, inventory management, and demand forecasting. Meanwhile, streaming services rely on AI for content personalization, language translation, and network optimization. As user bases grow and data volumes increase exponentially, these industries are scaling up their AI server capacities to ensure seamless and intelligent services, contributing steadily to market expansion.

The AI server market in China is projected to grow during the forecast period.  China’s expanding digital economy, particularly in sectors like e-commerce, fintech, and online entertainment, is also fueling AI server adoption. E-commerce platforms such as JD.com and Alibaba utilize AI servers to optimize logistics, manage dynamic pricing, and personalize user experiences. Similarly, fintech firms deploy AI for fraud detection, credit scoring, and intelligent customer support. Video streaming services use AI for content curation and real-time translation, which are computationally intensive and rely on high-throughput AI servers to ensure low latency and high availability.

Key AI Server Company Insights

Some key companies operating in the market Dell Inc. and IBM Corporation, among others, are some leading participants in the AI server market.

• Dell Inc. is an information technology solutions company providing a comprehensive portfolio that spans personal computers, servers, storage systems, networking equipment, software, and cloud services. The company's PowerEdge server lineup, particularly the XE series, is engineered to accelerate deep learning and AI tasks. For instance, the PowerEdge XE9680 server is designed for high-performance AI, machine learning, and deep learning workloads, enabling rapid development, training, and deployment of large machine learning models. It is the industry's first server to ship with eight NVIDIA H100 GPUs and NVIDIA AI software. It provides enterprises with a highly refined, systemized, and scalable platform to achieve breakthroughs in natural language processing, recommender systems, data analytics, and more.

• IBM Corporation is an information technology services company. IBM has developed specialized hardware to meet the demanding requirements of AI workloads. The IBM Power Systems, particularly those based on the POWER9 and POWER10 processors, are engineered to accelerate deep learning and AI tasks. These systems incorporate advanced technologies such as PCIe 4.0, NVIDIA NVLink, and OpenCAPI, facilitating faster data movement and improved performance over traditional x86 architectures. The POWER9-based AC922 servers, for instance, have demonstrated nearly four times the deep-learning framework performance compared to x86 systems, making them suitable for applications ranging from scientific research to real-time fraud detection.

Super Micro Computer, Inc., and ADLINK Technology Inc. are some emerging market participants in the AI server market.

• Super Micro Computer, Inc. specializes in high-performance server and storage solutions. The company offers a comprehensive portfolio of GPU-accelerated systems, including its H12 and H14 series servers, which support the latest NVIDIA and AMD GPUs. These servers are engineered to deliver high-density computing power, essential for tasks such as deep learning, machine learning, and high-performance computing (HPC). Supermicro's AI platforms are designed with flexibility in mind, offering various form factors and cooling options, including air and liquid cooling, to accommodate different deployment scenarios.

• ADLINK Technology Inc. specializes in designing and manufacturing embedded computing products, including computer-on-modules, industrial motherboards, data acquisition modules, and complete systems. The MEC-AI7400 series is an AI edge server designed specifically for smart manufacturing applications. This server integrates various acceleration cards, including GPU, motion control, I/O, and image capture cards, within a compact and dustproof chassis. Such a design ensures durability and adaptability in industrial settings, facilitating real-time data analysis and intelligent decision-making on the factory floor.

Recent Developments

• In May 2025, Dell Inc. launched new servers powered by Nvidia's Blackwell Ultra chips to meet growing AI demand. The servers are offered in air- and liquid-cooled versions. They support up to 192 chips by default, with customization up to 256, enabling AI model training up to four times faster than before.

• In May 2025, NVIDIA Corporation launched the DGX Spark and DGX Station systems. These systems feature ConnectX-8 SuperNIC, which delivers networking speeds of up to 800 Gb/s, enabling high-speed connectivity and scalable performance. The DGX Station can function either as a powerful desktop workstation for a single user running complex AI models with local data or as a centralized compute resource accessible on-demand by multiple users. It also supports NVIDIA Multi-Instance GPU (MIG) technology, allowing the GPU to be partitioned into up to seven instances, each equipped with dedicated high-bandwidth memory, cache, and compute cores, creating a personal cloud environment ideal for AI development and data science teams.

• In April 2025, Fujitsu Limited partnered with Supermicro Inc. and Nidec Corporation to enhance data center energy efficiency. They are integrating Fujitsu’s liquid-cooling software, Supermicro’s high-performance GPU servers, and Nidec’s efficient liquid-cooling system to create AI server systems optimized for liquid cooling. This approach eliminates air cooling fans, cuts server power consumption, lowers noise, and reduces operating temperatures, boosting overall data center power usage effectiveness (PUE).

AI Server Market Report Scope

Global AI Server Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2030. For this study, Grand View Research has segmented the global AI server market report based on processor type, cooling technology, form factor, end use, and region.

• Processor Type Outlook (Revenue, USD Billion, 2018 - 2030)

  • GPU-based Servers

  • FPGA-based Servers

  • ASIC-based Servers

• Cooling Technology Outlook (Revenue, USD Billion, 2018 - 2030)

  • Air Cooling

  • Liquid Cooling

  • Hybrid Cooling

• Form Factor Outlook (Revenue, USD Billion, 2018 - 2030)

  • Rack-mounted Servers

  • Blade Servers

  • Tower Servers

• End Use Outlook (Revenue, USD Billion, 2018 - 2030)

  • IT & Telecommunication

  • BFSI

  • Retail & E-commerce

  • Healthcare & Pharmaceutical

  • Automotive

  • Others

• Regional Outlook (Revenue, USD Billion, 2018 - 2030)

  • North America

    • U.S.

    • Canada

    • Mexico

  • Europe

    • Germany

    • UK

    • France

  • Asia Pacific

    • China

    • India

    • Japan

    • South Korea

    • Australia

  • Latin America

    • Brazil

  • Middle East & Africa

    • UAE

    • Saudi Arabia

    • South Africa